66 Search Results

With the growing demand for realistic representations of chemical structures and the advent of exascale computing, the intelligent sampling of potential energy surfaces and efficient identification of global minima have become more essential but also more feasible. Building on prior studies demonstrating the efficiency of the Artificial Bee Colony (ABC) swarm intelligence algorithm, we report a hybrid metaheuristic framework that integrates the adaptive exploration capabilities of ABC coupled with the exploitation strengths of genetic algorithms (GA) in a scalable, Python-based implementation. The resulting tool, RANGE (Robust Adaptive Nature-inspired Global Explorer), provides seamless interfaces to multiple potential energy evaluators, either directlymore » or via widely used Python libraries, and is designed for high-performance computing environments. We describe the implementation details of RANGE and evaluate its performance, relative to ABC- or GA-alone based algorithms, on a variety of chemical systems, including molecular clusters and heterogeneous surfaces. In conclusion, our results demonstrate RANGE’s efficiency, robustness, and broad applicability in addressing challenging global optimization problems in computational chemistry and materials science.« less

Biobased 2,3-butanediol (2,3-BDO) is a valuable biomass-derived chemical due to its versatility in being transformed into a wide variety of products. However, the separation and purification of 2,3-BDO from fermentation broth remain a significant challenge owing to its high boiling point and hydrophilic nature. Herein, we developed a machine learning (ML)-based screening workflow that uses molecular calculations as training data and requires only a small number of experimental measurements for validation to identify alternative solvent candidates for the liquid–liquid extraction (LLE) of 2,3-BDO from aqueous solution. In particular, 130 density functional theory (DFT) calculations with the implicit solvation method notmore » only built a correlation between the computational partition coefficient and the experimental distribution coefficient of 2,3-BDO but also parameterized an Extra-Trees ML model to screen the distribution coefficient for a wider range of 6717 organic solvents. The experimental measurements of only 24 solvents were needed to validate the computational results. A list of 50 prioritized solvents was proposed for 2,3-BDO LLE, and seven additional experimental measurements were conducted to further verify our selected solvents. The impact of the extraction temperature and solvent-to-feed ratio was also investigated for selected solvents in experiments. Furthermore, this work suggested alternative solvents for 2,3-BDO LLE and proposed a versatile workflow that requires fewer experiments and can be applied to a broader range of LLE studies.« less

High entropy oxides (HEOs) have emerged as promising catalysts for several important chemical transformations including alkane activation. Hydrogen adsorption energy (HAE) has been used as a key descriptor for many reactions including methane C–H activation and hydrogen evolution reactions. Hence, understanding the relationship between HAEs and the surface chemistry of HEO surfaces could lay the foundation for meaningful correlations among methane C–H activation, HAE, and the complex, local environment of HEO surfaces. Here, we used a medium-entropy oxide as a prototypical system – Mg_0.25Ni_0.25Cu_0.25Zn_0.25O with a rock-salt structure – to interrogate these relationships. We sampled 2000 different surfaces of itsmore » (100) plane and calculated the HAEs at randomly chosen surface O sites using density functional theory (DFT). Our analysis of the 2000 data points reveals that the HAEs at the surface O sites are significantly influenced by the local environment around the adsorption sites, particularly the nature of the metal atom directly below the surface O site where H adsorbs. After comparing several popular graph-neural-network-based machine learning models, we found that the DimeNet++ model performed best achieving satisfactory accuracy in predicting HAEs for both Mg_0.25Ni_0.25Cu_0.25Zn_0.25O and slightly varied compositions. Our work underscores the promise of such models and the need for further refinement to address the complexity of HEOs.« less

Understanding the quantitative interactions among zeolite pore walls, Bro̷nsted acid sites, and molecules with both polar and nonpolar regions is essential for scoping out the potential of zeolites as sorbents and catalysts. Purely siliceous zeolites (MFI and Beta in the present study) are hydrophobic, whereas those containing aluminum are considered hydrophilic, preferentially adsorbing organic molecules even in aqueous environments. To characterize these interactions, we use primary alcohols of increasing molecular weight, quantifying their specific interactions in the confined pore space of the alkyl (CH_x) and OH groups. Three types of interactions were identified: (i) alkyl CH_x groups interacting with themore » zeolite pore walls (approximately 10 kJ mol⁻¹ per carbon), (ii) alcohol OH groups interacting with the pore walls (30−35 kJ mol⁻¹), and (iii) alcohol OH groups interacting with Bro̷nsted acid sites (37 kJ mol⁻¹). All three interactions were well mirrored by computational simulations. The contribution of the alkyl CH_x groups was inferred from the incremental increase in sorption enthalpy with increasing molecular weight; the interaction strength of the OH groups was determined by extrapolating the global adsorption enthalpy of the alcohols to a hypothetical OH group without an alkyl group. This value was identical to the adsorption enthalpy of water. The experiments demonstrated that only water has an adsorption enthalpy on zeolite pore walls lower than its condensation enthalpy (30−35 kJ mol⁻¹ vs 45 kJ mol⁻¹), limiting the concentration of water that can be adsorbed.« less

Molecular-level insights into reactive separations are crucial for the design of new conversion pathways of carbon dioxide (CO₂). This work explores a postulated pathway that directs CO₂ to undergo inverse-electron-demand Diels–Alder reactions to produce heterocycles using the CO₂ chemically fixed on water-lean solvent molecules. Density functional theory calculations are applied to evaluate the lowest unoccupied molecular orbital (LUMO) energies of three types of reactants (1,3-butadiene, 1,3-cyclohexadiene, and 1,2,4,5-tetrazine) with various functional substituents. These calculations also provide a data set (5.8k data) for developing a machine learning model to efficiently predict LUMO energies. A computational screening of LUMO energies for anmore » additional 47k diene and tetrazine candidates is performed, and a list of candidates with lowered LUMO energies by electron-withdrawing substituents is provided. These candidates are further examined by their reaction energy barriers computed from the interatomic potential or density functional theory. Two major energy barriers are identified, one for the proton transfer within the water-lean solvent and the other for the CO₂ transfer from the solvent molecule to the reactant candidate (diene or tetrazine). The functional substituents have a more significant impact on the second barrier but a very slight one on the first barrier. This exploratory work demonstrates a new possibility for guiding experimental efforts toward the chemical conversion of fixated CO₂ to value-added compounds.« less

Although it has been established that covalent functionalization of the U–O bonds in the uranyl dication (UO₂²⁺) generally requires use of strong reductants and electrophiles, little work has examined how interactions between the individual reaction components could affect final outcomes in solution. Here, the patterns of such reactivity have been studied in a UO₂²⁺-containing model system supported by a workhorse pentadentate ligand, 2,2′-[(methylimino)bis(2,1-ethanediylnitrilomethylidyne)]bis-phenol. Oxo activation and functionalization have been tested with (i) electrochemical and chemical reduction, and (ii) coordinating and noncoordinating solvents. In acetonitrile, uranyl reduction was achieved cleanly, but treatment of the reduced species with tris(pentafluorophenyl)borane (BCF) resulted inmore » a mixture of products arising from direct electron transfer to BCF. In dichloromethane (CH₂Cl₂), electrochemical reduction of uranyl was achieved cleanly, but clean chemical reactivity was inaccessible. Despite these challenges, one trinuclear and oxo-deficient uranium-containing product was crystallized from CH₂Cl₂ solution and characterized; thus, desirable electrophilic reactivity can proceed to some degree in CH₂Cl₂ with BCF. Computational studies were used to investigate the properties of the trinuclear uranium product and the changes that could be inducible by further reduction. Here, taken together, the reactivity patterns identified here could inform design of improved systems for actinyl oxo functionalization.« less

As the chemical industry shifts toward sustainable practices, there is a growing initiative to replace conventional fossil-derived solvents with environmentally friendly alternatives such as ionic liquids (ILs) and deep eutectic solvents (DESs). Artificial intelligence (AI) plays a key role in the discovery and design of novel solvents and the development of green processes. This review explores the latest advancements in AI-assisted solvent screening with a specific focus on machine learning (ML) models for physicochemical property prediction and separation process design. Additionally, this paper highlights recent progress in the development of automated high-throughput (HT) platforms for solvent screening. Finally, this papermore » discusses the challenges and prospects of ML-driven HT strategies for green solvent design and optimization. To this end, this review provides key insights to advance solvent screening strategies for future chemical and separation processes.« less

Ensemble-average sampling of structures from ab initio molecular dynamics (AIMD) simulations can be used to predict theoretical extended X-ray absorption fine structure (EXAFS) signals that closely match experimental spectra. However, AIMD simulations are time-consuming and resource-intensive, particularly for solvated lanthanide ions, which often form multiple nonrigid geometries with high coordination numbers. Here, to accelerate the characterization of lanthanide structures in solution, we employed the Northwest Potential Energy Surface Search Engine (NWPEsSe), an adaptive-learning global optimization algorithm, to efficiently screen first-shell structures. As case studies, we examine two systems: Eu(NO₃)₃ dissolved in acetonitrile with a terpyridine ligand (terpyNO₂), and Nd(NO₃)₃ dissolvedmore » in acetonitrile. The theoretical spectra for structures identified by NWPEsSe were compared to both experimental and AIMD-derived EXAFS spectra. The NWPEsSe algorithm successfully identified the proper solvation structure for both Eu(NO₃)₃(terpyNO₂) and Nd(NO₃)(acetonitrile)₃, with the calculated EXAFS signals closely matching the experimental spectra for the Eu-ligand complex and showing good similarity for the Nd salt; the better agreement with the ligand-containing structure is attributed to a less dynamic coordination environment due to the rigid ligand. The key advantage of the global optimization algorithm lies in its ability to sample the coordination environment across the potential energy surface and reduce the time required to identify structures from generally a month to within a week. Additionally, this approach is versatile and can be adapted to characterize main-group metal complexes.« less

Membrane separation for 2,3-butanediol (2,3-BDO) recovery from fermentation broth is highly valued for sustainable and renewable processes, but it requires efficient membrane materials. Here, this work evaluates the sulfonated polybenzimidazole (sPBI) and its graphene oxide (GO) doped composite membrane for separating 2,3-BDO and water via atomistic simulations. Density functional theory calculations are applied to identify various forms of sPBI structures and quantify their binding interactions with 2,3-BDO and water. Classical molecular dynamic simulations are used to evaluate the structural changes, diffusivity, and selectivity of 2,3-BDO and water in different sPBI models, GO surfaces, and GO-doped sPBI composite models. Our resultsmore » suggest that sPBI slightly increases the crystallinity of the membrane structures, enhances the adsorption strength for both 2,3-BDO and water, and improves the water/2,3-BDO selectivity by 2–3 times. The GO surfaces display a maximum selectivity at a surface coverage of 0.1–0.15 for both hydroxyl and epoxy surface groups. The addition of GO flakes to sPBI creates new interaction sites for 2,3-BDO and water at the interface of sPBI and GO, and the water/2,3-BDO selectivity of GO-doped sPBI models is further increased up to 3 times. This work illustrates how the integrated addition of sPBI and GO flakes offers a promising approach to selective separation of 2,3-BDO and water, providing theoretical guidance for polybenzimidazole-based membranes in the potential application of 2,3-BDO recovery.« less

Nitrogen oxides, present in flue gas, can cause negative impacts on amine carbon capture solvents by the formation of heat-stable salts and suspected carcinogens. Thus, to maximize the performance of water-lean solvents, a better understanding of this process in these systems is necessary. Here, a computational study for the fixation of the CO₂ capture solvent N-(2-ethoxyethyl)-3-morpholinopropan-1-amine (EEMPA) to nitramine/nitrosamine was conducted. The first step involves the dissociation of the NH bond of EEMPA, in which the homolytic mechanism is energetically more favorable than the heterolytic mechanism. The second step involves radical recombination to form N–N bonds. While NO₂ directly reactsmore » with EEMPA, NO has almost no effect. However, in the presence of O₂, fixation of EEMPA by NO is enhanced via the formation of N₂O₄ species. Finally, low reaction energies indicate that the formation of nitramine/nitrosamine may be a reversible process, suggesting that EEMPA could be recovered under thermal stripping conditions.« less